----------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/parkerrogers/Dropbox/MedicalInnovationProjects/CivilWarProject/Restat_Replication/LogFiles/W
> arsAndProsthesisPatentsAnalysisOfCountsEventStudies.log
  log type:  text
 opened on:  19 May 2023, 09:58:32

. 
. 
. 
. **** Assemble data for additional figures and regressions
. use "Data/control_classes_CW.dta", clear

. append using "Data/control_classes_WWI.dta"

. merge 1:1 patnum using "Data/all_patents_basicinfo.dta"

    Result                           # of obs.
    -----------------------------------------
    not matched                     8,164,168
        from master                         0  (_merge==1)
        from using                  8,164,168  (_merge==2)

    matched                           745,558  (_merge==3)
    -----------------------------------------

. keep if _merge == 3
(8,164,168 observations deleted)

. drop _merge

. 
. tab iyear if nclassgoogle1 == 623

      iyear |      Freq.     Percent        Cum.
------------+-----------------------------------
       1846 |          1        0.12        0.12
       1849 |          1        0.12        0.25
       1850 |          1        0.12        0.37
       1852 |          3        0.37        0.74
       1855 |          3        0.37        1.11
       1856 |          3        0.37        1.47
       1857 |          4        0.49        1.97
       1858 |          1        0.12        2.09
       1859 |          7        0.86        2.95
       1860 |          2        0.25        3.19
       1861 |          1        0.12        3.32
       1862 |          4        0.49        3.81
       1863 |         15        1.84        5.65
       1864 |         18        2.21        7.86
       1865 |         27        3.32       11.18
       1866 |         17        2.09       13.27
       1867 |         10        1.23       14.50
       1868 |          5        0.61       15.11
       1869 |          7        0.86       15.97
       1870 |          1        0.12       16.09
       1871 |          4        0.49       16.58
       1872 |          2        0.25       16.83
       1873 |          1        0.12       16.95
       1874 |          1        0.12       17.08
       1875 |          3        0.37       17.44
       1876 |          1        0.12       17.57
       1877 |          4        0.49       18.06
       1879 |          1        0.12       18.18
       1880 |          2        0.25       18.43
       1881 |          1        0.12       18.55
       1882 |          2        0.25       18.80
       1883 |          5        0.61       19.41
       1884 |          7        0.86       20.27
       1885 |          9        1.11       21.38
       1886 |          5        0.61       21.99
       1887 |          6        0.74       22.73
       1888 |          2        0.25       22.97
       1889 |          7        0.86       23.83
       1890 |         10        1.23       25.06
       1900 |          8        0.98       26.04
       1901 |          9        1.11       27.15
       1902 |         14        1.72       28.87
       1903 |         13        1.60       30.47
       1904 |         15        1.84       32.31
       1905 |         12        1.47       33.78
       1906 |         21        2.58       36.36
       1907 |          7        0.86       37.22
       1908 |          5        0.61       37.84
       1909 |          7        0.86       38.70
       1910 |         14        1.72       40.42
       1911 |         13        1.60       42.01
       1912 |         12        1.47       43.49
       1913 |         20        2.46       45.95
       1914 |         16        1.97       47.91
       1915 |         10        1.23       49.14
       1916 |         13        1.60       50.74
       1917 |         20        2.46       53.19
       1918 |         37        4.55       57.74
       1919 |         43        5.28       63.02
       1920 |         28        3.44       66.46
       1921 |         39        4.79       71.25
       1922 |         27        3.32       74.57
       1923 |         14        1.72       76.29
       1924 |         22        2.70       78.99
       1925 |         10        1.23       80.22
       1926 |         15        1.84       82.06
       1927 |         15        1.84       83.91
       1928 |          9        1.11       85.01
       1929 |         10        1.23       86.24
       1930 |          5        0.61       86.86
       1931 |         10        1.23       88.08
       1932 |         12        1.47       89.56
       1933 |         13        1.60       91.15
       1934 |          6        0.74       91.89
       1935 |         17        2.09       93.98
       1936 |          9        1.11       95.09
       1937 |         15        1.84       96.93
       1938 |          5        0.61       97.54
       1939 |          9        1.11       98.65
       1940 |         11        1.35      100.00
------------+-----------------------------------
      Total |        814      100.00

. 
. 
. rename iyear year

. 
. 
. gen patentcount = 1

. 
. 
. collapse (sum) patentcount, by(nclassgoogle1 year)

. 
. tsset nclassgoogle1 year
       panel variable:  nclassgoogle1 (unbalanced)
        time variable:  year, 1840 to 1940, but with gaps
                delta:  1 unit

. tsfill

. 
. drop if year < 1850
(913 observations deleted)

. 
. gen eventyear = . 
(10,989 missing values generated)

. replace eventyear = year - 1862 if year <= 1890
(4,889 real changes made)

. replace eventyear = year - 1915 if year > 1890
(6,100 real changes made)

. 
. 
. *** Generate a numeric variable for the individual war episodes
. gen warepisode = .
(10,989 missing values generated)

. replace warepisode = 1 if year >= 1840 & year <= 1890
(4,889 real changes made)

. replace warepisode = 2 if year >= 1890 & year <= 1940
(6,222 real changes made)

. 
. egen class_by_episode = group(nclassgoogle1 warepisode)

. egen class_by_episodecount = count(class_by_episode), by(class_by_episode)

. tab class_by_episodecount if warepisode == 1

class_by_ep |
 isodecount |      Freq.     Percent        Cum.
------------+-----------------------------------
         12 |         12        0.25        0.25
         20 |         20        0.42        0.67
         25 |         25        0.52        1.20
         29 |         29        0.61        1.80
         31 |         31        0.65        2.45
         33 |         66        1.38        3.84
         34 |         34        0.71        4.55
         35 |         35        0.73        5.29
         37 |         37        0.78        6.06
         39 |         78        1.64        7.70
         40 |      4,400       92.30      100.00
------------+-----------------------------------
      Total |      4,767      100.00

. tab class_by_episodecount if warepisode == 2

class_by_ep |
 isodecount |      Freq.     Percent        Cum.
------------+-----------------------------------
         51 |      6,222      100.00      100.00
------------+-----------------------------------
      Total |      6,222      100.00

. keep if (class_by_episodecount == 40 & warepisode == 1) | (class_by_episodecount == 51 & warepisode == 2)
(367 observations deleted)

. 
. tsset class_by_episode eventyear
       panel variable:  class_by_episode (unbalanced)
        time variable:  eventyear, -24 to 28, but with gaps
                delta:  1 unit

. 
. replace patentcount = 0 if patentcount == .
(1,484 real changes made)

. egen premeanpatentsperyearB = mean(patentcount) if eventyear < 0, by(class_by_episode)
(6,374 missing values generated)

. egen premeanpatentsperyear = max(premeanpatentsperyearB), by(class_by_episode)

. 
. drop if premeanpatentsperyear <= 1
(971 observations deleted)

. 
. drop if eventyear < -12
(1,452 observations deleted)

. drop if eventyear > 15
(2,375 observations deleted)

. 
. *** Create key treatment variable
. gen prosthetics = 0

. replace prosthetics = 1 if nclassgoogle1 == 623
(56 real changes made)

. 
. *** Create Alternative Control Groups
. gen medicalclass = 0

. replace medicalclass = 1 if inlist(nclassgoogle1, 424, 514, 128, 600, 601, 602, 604, 606, 607, 435, 800, 351, 
> 433, 623)
(448 real changes made)

. gen miscmechanical = 0

. replace miscmechanical = 1 if inlist(nclassgoogle1, 7, 16, 42, 49, 51, 74, 81, 86, 89, 100, 124, 157, 184, 193
> , 194, 198, 212, 227, 235, 239, 254, 267, 291, 294, 384, 400, 402, 406, 411, 453, 454, 470, 482, 483, 492, 508
> )
(1,596 real changes made)

. gen metalworkmechanical = 0

. replace metalworkmechanical = 1 if inlist(nclassgoogle1, 29, 72, 75, 76, 140, 147, 148, 163, 164, 228, 266, 27
> 0, 413, 419, 420)
(700 real changes made)

. gen materialprocessingmechanical = 0

. replace materialprocessingmechanical = 1 if inlist(nclassgoogle1, 65, 82, 83, 125, 141, 142, 144, 173, 209, 22
> 1, 225, 226, 234, 241, 242, 264, 271, 407, 408, 409, 414, 425, 451, 493)
(1,232 real changes made)

. 
. sum *

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
        year |      5,824    1894.332    27.36539       1850       1930
nclassgoog~1 |      5,824     265.149    153.2053          7        623
 patentcount |      5,824    82.49451    107.1251          0        938
   eventyear |      5,824         1.5    8.078441        -12         15
  warepisode |      5,824    1.581731    .4933172          1          2
-------------+---------------------------------------------------------
class_by_e~e |      5,824    119.4375    71.03877          2        244
class_by_e~t |      5,824    46.39904    5.426489         40         51
premeanpat~B |      2,496     42.3736    54.13136       1.25      272.5
premeanpat~r |      5,824     42.3736    54.12516       1.25      272.5
 prosthetics |      5,824    .0096154    .0975939          0          1
-------------+---------------------------------------------------------
medicalclass |      5,824    .0769231    .2664922          0          1
miscmechan~l |      5,824    .2740385    .4460668          0          1
metalworkm~l |      5,824    .1201923    .3252142          0          1
materialpr~l |      5,824    .2115385    .4084343          0          1

. 
. replace eventyear = eventyear + 100
(5,824 real changes made)

. fvset base 100 eventyear

. 
. // Generates Figure D.1
. poisson patentcount i.prosthetics##i.eventyear i.eventyear##i.warepisode i.nclassgoogle1##i.warepisode , clust
> er(class_by_episode)
note: 623.nclassgoogle1 omitted because of collinearity
note: 7.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 51.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 51.nclassgoogle1#2.warepisode omitted because of collinearity
note: 123.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 123.nclassgoogle1#2.warepisode omitted because of collinearity
note: 124.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 124.nclassgoogle1#2.warepisode omitted because of collinearity
note: 152.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 152.nclassgoogle1#2.warepisode omitted because of collinearity
note: 157.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 157.nclassgoogle1#2.warepisode omitted because of collinearity
note: 193.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 193.nclassgoogle1#2.warepisode omitted because of collinearity
note: 194.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 194.nclassgoogle1#2.warepisode omitted because of collinearity
note: 225.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 225.nclassgoogle1#2.warepisode omitted because of collinearity
note: 226.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 226.nclassgoogle1#2.warepisode omitted because of collinearity
note: 234.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 234.nclassgoogle1#2.warepisode omitted because of collinearity
note: 258.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 258.nclassgoogle1#2.warepisode omitted because of collinearity
note: 270.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 270.nclassgoogle1#2.warepisode omitted because of collinearity
note: 291.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 291.nclassgoogle1#2.warepisode omitted because of collinearity
note: 293.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 293.nclassgoogle1#2.warepisode omitted because of collinearity
note: 303.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 303.nclassgoogle1#2.warepisode omitted because of collinearity
note: 305.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 305.nclassgoogle1#2.warepisode omitted because of collinearity
note: 351.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 351.nclassgoogle1#2.warepisode omitted because of collinearity
note: 352.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 352.nclassgoogle1#2.warepisode omitted because of collinearity
note: 353.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 353.nclassgoogle1#2.warepisode omitted because of collinearity
note: 355.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 355.nclassgoogle1#2.warepisode omitted because of collinearity
note: 400.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 400.nclassgoogle1#2.warepisode omitted because of collinearity
note: 402.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 402.nclassgoogle1#2.warepisode omitted because of collinearity
note: 406.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 406.nclassgoogle1#2.warepisode omitted because of collinearity
note: 407.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 407.nclassgoogle1#2.warepisode omitted because of collinearity
note: 410.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 410.nclassgoogle1#2.warepisode omitted because of collinearity
note: 413.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 413.nclassgoogle1#2.warepisode omitted because of collinearity
note: 419.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 419.nclassgoogle1#2.warepisode omitted because of collinearity
note: 453.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 453.nclassgoogle1#2.warepisode omitted because of collinearity
note: 482.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 482.nclassgoogle1#2.warepisode omitted because of collinearity
note: 492.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 492.nclassgoogle1#2.warepisode omitted because of collinearity
note: 600.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 600.nclassgoogle1#2.warepisode omitted because of collinearity
note: 601.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 601.nclassgoogle1#2.warepisode omitted because of collinearity
note: 607.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 607.nclassgoogle1#2.warepisode omitted because of collinearity
note: 623.nclassgoogle1#2.warepisode omitted because of collinearity

Iteration 0:   log pseudolikelihood = -542766.81  
Iteration 1:   log pseudolikelihood = -273999.84  
Iteration 2:   log pseudolikelihood =  -45786.31  
Iteration 3:   log pseudolikelihood = -36823.157  
Iteration 4:   log pseudolikelihood = -36609.943  
Iteration 5:   log pseudolikelihood = -36609.424  
Iteration 6:   log pseudolikelihood = -36609.424  

Poisson regression                              Number of obs     =      5,824
                                                Wald chi2(54)     =          .
Log pseudolikelihood = -36609.424               Prob > chi2       =          .

                                 (Std. Err. adjusted for 208 clusters in class_by_episode)
------------------------------------------------------------------------------------------
                         |               Robust
             patentcount |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
           1.prosthetics |  -1.127417    .228259    -4.94   0.000    -1.574797    -.680038
                         |
               eventyear |
                     88  |  -1.171528   .1189342    -9.85   0.000    -1.404635   -.9384213
                     89  |  -1.239261   .1205042   -10.28   0.000    -1.475445   -1.003077
                     90  |   -1.16322   .1268078    -9.17   0.000    -1.411759   -.9146811
                     91  |  -1.213036   .1183265   -10.25   0.000    -1.444952   -.9811203
                     92  |  -.3965719   .1112926    -3.56   0.000    -.6147013   -.1784425
                     93  |  -.3186704    .101619    -3.14   0.002    -.5178399   -.1195009
                     94  |  -.1682848   .1057442    -1.59   0.112    -.3755396    .0389699
                     95  |  -.0930608   .1003966    -0.93   0.354    -.2898346     .103713
                     96  |   .0993604   .0916155     1.08   0.278    -.0802027    .2789235
                     97  |   .3167089    .083051     3.81   0.000      .153932    .4794858
                     98  |   .3000165    .085486     3.51   0.000      .132467    .4675661
                     99  |  -.0840356   .0506085    -1.66   0.097    -.1832265    .0151553
                    101  |   .2070583   .0433486     4.78   0.000     .1220966    .2920201
                    102  |   .3896309   .0488946     7.97   0.000     .2937992    .4854626
                    103  |   .6233553   .0706682     8.82   0.000     .4848482    .7618624
                    104  |   .9419991   .0859023    10.97   0.000     .7736336    1.110365
                    105  |   1.288094   .0995789    12.94   0.000     1.092923    1.483265
                    106  |   1.295844    .104025    12.46   0.000     1.091959    1.499729
                    107  |    1.34239    .099007    13.56   0.000      1.14834     1.53644
                    108  |   1.266546   .0955915    13.25   0.000      1.07919    1.453902
                    109  |   1.252199   .0926978    13.51   0.000     1.070515    1.433883
                    110  |   1.302982   .0990837    13.15   0.000     1.108782    1.497183
                    111  |   1.275419   .0999513    12.76   0.000     1.079518     1.47132
                    112  |   1.352584   .1033597    13.09   0.000     1.150003    1.555166
                    113  |   1.382767   .0954102    14.49   0.000     1.195766    1.569767
                    114  |   1.409935   .0989664    14.25   0.000     1.215964    1.603905
                    115  |   1.278196   .0940349    13.59   0.000     1.093891    1.462501
                         |
   prosthetics#eventyear |
                  1  88  |    .429192   .2158316     1.99   0.047     .0061698    .8522142
                  1  89  |   .4990585   .3104883     1.61   0.108    -.1094873    1.107604
                  1  90  |   .5068369   .0572692     8.85   0.000     .3945913    .6190825
                  1  91  |   .7783213   .3082773     2.52   0.012     .1741089    1.382534
                  1  92  |  -.4902572   .3758526    -1.30   0.192    -1.226915    .2464003
                  1  93  |  -.2640521   .1370212    -1.93   0.054    -.5326086    .0045045
                  1  94  |  -.1593239   .0456672    -3.49   0.000    -.2488299   -.0698178
                  1  95  |   .4552151   .1163917     3.91   0.000     .2270915    .6833387
                  1  96  |   .2150843   .3710685     0.58   0.562    -.5121966    .9423652
                  1  97  |   .3978047   .0431037     9.23   0.000     .3133231    .4822863
                  1  98  |   .6176923   .3828455     1.61   0.107     -.132671    1.368056
                  1  99  |   .2786496   .3223387     0.86   0.387    -.3531226    .9104219
                  1 101  |   .6624921   .3203673     2.07   0.039     .0345838      1.2904
                  1 102  |   1.015213   .1779919     5.70   0.000     .6663554    1.364071
                  1 103  |   1.529963    .043369    35.28   0.000     1.444961    1.614964
                  1 104  |   1.388311    .253616     5.47   0.000     .8912333     1.88539
                  1 105  |   .8283274   .3987997     2.08   0.038     .0466944     1.60996
                  1 106  |   .9598612   .6064428     1.58   0.113    -.2287448    2.148467
                  1 107  |   .6736911    .485931     1.39   0.166    -.2787162    1.626098
                  1 108  |  -.1157287   .6576899    -0.18   0.860    -1.404777     1.17332
                  1 109  |   .3915712   .5053394     0.77   0.438    -.5988758    1.382018
                  1 110  |  -.4272586   .4900149    -0.87   0.383     -1.38767     .533153
                  1 111  |  -.0948928   .6459055    -0.15   0.883    -1.360844    1.171059
                  1 112  |  -.0837108   .6925843    -0.12   0.904    -1.441151    1.273729
                  1 113  |   -.369555   .4453817    -0.83   0.407    -1.242487    .5033772
                  1 114  |  -.4935083   .6651309    -0.74   0.458    -1.797141    .8101244
                  1 115  |  -.6580412   .1191474    -5.52   0.000    -.8915659   -.4245166
                         |
            2.warepisode |   2.024032   .1330177    15.22   0.000     1.763323    2.284742
                         |
    eventyear#warepisode |
                   88 2  |   .8092764   .1286238     6.29   0.000     .5571783    1.061374
                   89 2  |   .8799327   .1313161     6.70   0.000     .6225579    1.137308
                   90 2  |   .7913095   .1364901     5.80   0.000     .5237938    1.058825
                   91 2  |   .9125876   .1297973     7.03   0.000     .6581896    1.166986
                   92 2  |   .2166794   .1193065     1.82   0.069     -.017157    .4505158
                   93 2  |   .0261201   .1110397     0.24   0.814    -.1915137    .2437539
                   94 2  |  -.0100405   .1149275    -0.09   0.930    -.2352943    .2152133
                   95 2  |  -.1264478   .1074122    -1.18   0.239    -.3369718    .0840761
                   96 2  |  -.3644954   .0999247    -3.65   0.000    -.5603442   -.1686465
                   97 2  |  -.4782558   .0911135    -5.25   0.000     -.656835   -.2996765
                   98 2  |  -.5473354   .0932713    -5.87   0.000    -.7301438   -.3645269
                   99 2  |  -.0005185   .0556879    -0.01   0.993    -.1096648    .1086277
                  101 2  |  -.2022225   .0472039    -4.28   0.000    -.2947404   -.1097046
                  102 2  |  -.4748395   .0522458    -9.09   0.000    -.5772394   -.3724397
                  103 2  |  -.7577175   .0756212   -10.02   0.000    -.9059323   -.6095028
                  104 2  |  -1.079381   .0923767   -11.68   0.000    -1.260436   -.8983258
                  105 2  |  -1.435291   .1043966   -13.75   0.000    -1.639905   -1.230677
                  106 2  |  -1.423932   .1095748   -13.00   0.000    -1.638695    -1.20917
                  107 2  |   -1.45227   .1051061   -13.82   0.000    -1.658274   -1.246265
                  108 2  |  -1.379752   .1018987   -13.54   0.000     -1.57947   -1.180034
                  109 2  |  -1.293938   .1003862   -12.89   0.000    -1.490691   -1.097185
                  110 2  |  -1.301569   .1074194   -12.12   0.000    -1.512107   -1.091031
                  111 2  |   -1.32711   .1083463   -12.25   0.000    -1.539465   -1.114755
                  112 2  |  -1.462559   .1105358   -13.23   0.000    -1.679205   -1.245912
                  113 2  |  -1.513312   .1053574   -14.36   0.000    -1.719809   -1.306815
                  114 2  |  -1.497719   .1115622   -13.42   0.000    -1.716377   -1.279061
                  115 2  |  -1.349655   .1087341   -12.41   0.000     -1.56277    -1.13654
                         |
           nclassgoogle1 |
                     16  |   1.648779    .106343    15.50   0.000     1.440351    1.857208
                     29  |   .6755611    .106343     6.35   0.000     .4671325    .8839896
                     42  |   1.672081    .106343    15.72   0.000     1.463653     1.88051
                     49  |   1.723214    .106343    16.20   0.000     1.514786    1.931643
                     51  |  -1.373335   2.40e-13 -5.7e+12   0.000    -1.373335   -1.373335
                     65  |   -.181023    .106343    -1.70   0.089    -.3894515    .0274055
                     72  |   2.005716    .106343    18.86   0.000     1.797287    2.214145
                     74  |   2.088786    .106343    19.64   0.000     1.880357    2.297214
                     75  |   .5999855    .106343     5.64   0.000      .391557    .8084141
                     76  |   1.114543    .106343    10.48   0.000      .906114    1.322971
                     81  |   1.296864    .106343    12.20   0.000     1.088436    1.505293
                     82  |   .3411664    .106343     3.21   0.001     .1327379    .5495949
                     83  |   2.383926    .106343    22.42   0.000     2.175498    2.592355
                     86  |  -.6453286    .106343    -6.07   0.000    -.8537571   -.4369001
                     89  |   .3603516    .106343     3.39   0.001     .1519231    .5687802
                     91  |   1.330735    .106343    12.51   0.000     1.122306    1.539163
                     92  |   .3484041    .106343     3.28   0.001     .1399755    .5568326
                    100  |   1.599792    .106343    15.04   0.000     1.391364    1.808221
                    104  |    .336312    .106343     3.16   0.002     .1278835    .5447406
                    105  |   1.241347    .106343    11.67   0.000     1.032919    1.449776
                    114  |   1.668235    .106343    15.69   0.000     1.459806    1.876664
                    123  |    2.74755   2.40e-13  1.1e+13   0.000      2.74755     2.74755
                    124  |  -.0547317   2.40e-13 -2.3e+11   0.000    -.0547317   -.0547317
                    125  |   .4873295    .106343     4.58   0.000      .278901    .6957581
                    128  |    .381504    .106343     3.59   0.000     .1730755    .5899325
                    140  |  -.9460827    .106343    -8.90   0.000    -1.154511   -.7376542
                    141  |  -.0655101    .106343    -0.62   0.538    -.2739386    .1429184
                    142  |   .1378017    .106343     1.30   0.195    -.0706268    .3462303
                    144  |   2.096349    .106343    19.71   0.000      1.88792    2.304777
                    147  |   .2230806    .106343     2.10   0.036     .0146521    .4315092
                    148  |  -.2100105    .106343    -1.97   0.048    -.4184391    -.001582
                    152  |   2.469664   2.40e-13  1.0e+13   0.000     2.469664    2.469664
                    157  |  -.0616442   2.40e-13 -2.6e+11   0.000    -.0616442   -.0616442
                    164  |   .7163137    .106343     6.74   0.000     .5078852    .9247423
                    173  |  -.1371038    .106343    -1.29   0.197    -.3455323    .0713248
                    180  |  -1.117933    .106343   -10.51   0.000    -1.326362   -.9095045
                    184  |   .3387422    .106343     3.19   0.001     .1303136    .5471707
                    185  |   .6807469    .106343     6.40   0.000     .4723184    .8891754
                    187  |   .1926495    .106343     1.81   0.070     -.015779    .4010781
                    188  |   1.391836    .106343    13.09   0.000     1.183407    1.600264
                    192  |   .2657538    .106343     2.50   0.012     .0573253    .4741823
                    193  |   .0086581   2.40e-13  3.6e+10   0.000     .0086581    .0086581
                    194  |    .983543   2.40e-13  4.1e+12   0.000      .983543     .983543
                    198  |   .1466644    .106343     1.38   0.168    -.0617641     .355093
                    209  |   1.981126    .106343    18.63   0.000     1.772698    2.189555
                    212  |    .175652    .106343     1.65   0.099    -.0327766    .3840805
                    213  |   1.706665    .106343    16.05   0.000     1.498236    1.915093
                    221  |  -.7623003    .106343    -7.17   0.000    -.9707288   -.5538717
                    225  |  -.5036054   2.40e-13 -2.1e+12   0.000    -.5036054   -.5036054
                    226  |  -.1897403   2.40e-13 -7.9e+11   0.000    -.1897403   -.1897403
                    227  |   .2038228    .106343     1.92   0.055    -.0046057    .4122514
                    228  |  -.2573312    .106343    -2.42   0.016    -.4657597   -.0489026
                    234  |  -.8582269   2.40e-13 -3.6e+12   0.000    -.8582269   -.8582269
                    235  |   .5018677    .106343     4.72   0.000     .2934392    .7102962
                    238  |   .8687991    .106343     8.17   0.000     .6603706    1.077228
                    239  |   .8843912    .106343     8.32   0.000     .6759627     1.09282
                    241  |   2.013022    .106343    18.93   0.000     1.804593     2.22145
                    242  |    .822007    .106343     7.73   0.000     .6135784    1.030436
                    244  |  -1.097314    .106343   -10.32   0.000    -1.305742   -.8888852
                    246  |   1.055871    .106343     9.93   0.000     .8474428      1.2643
                    251  |    1.20731    .106343    11.35   0.000     .9988816    1.415739
                    254  |   1.730483    .106343    16.27   0.000     1.522054    1.938911
                    258  |   .2581749   2.40e-13  1.1e+12   0.000     .2581749    .2581749
                    264  |  -.0875698    .106343    -0.82   0.410    -.2959984    .1208587
                    266  |   .1554492    .106343     1.46   0.144    -.0529793    .3638778
                    267  |   1.214413    .106343    11.42   0.000     1.005985    1.422842
                    270  |  -.3275987   2.40e-13 -1.4e+12   0.000    -.3275987   -.3275987
                    271  |  -.7478073    .106343    -7.03   0.000    -.9562358   -.5393787
                    280  |   1.940872    .106343    18.25   0.000     1.732443      2.1493
                    291  |  -.5998152   2.40e-13 -2.5e+12   0.000    -.5998152   -.5998152
                    293  |   1.100784   2.40e-13  4.6e+12   0.000     1.100784    1.100784
                    294  |   1.390141    .106343    13.07   0.000     1.181712    1.598569
                    295  |   .2203521    .106343     2.07   0.038     .0119236    .4287807
                    296  |   .7776233    .106343     7.31   0.000     .5691947    .9860518
                    298  |  -.4041665    .106343    -3.80   0.000    -.6125951    -.195738
                    301  |   1.255033    .106343    11.80   0.000     1.046604    1.463461
                    303  |   .9223592   2.40e-13  3.8e+12   0.000     .9223592    .9223592
                    305  |  -.2690168   2.40e-13 -1.1e+12   0.000    -.2690168   -.2690168
                    351  |   .7800227   2.40e-13  3.3e+12   0.000     .7800227    .7800227
                    352  |   .7810187   2.40e-13  3.3e+12   0.000     .7810187    .7810187
                    353  |  -.4493489   2.40e-13 -1.9e+12   0.000    -.4493489   -.4493489
                    355  |   .1668032   2.40e-13  7.0e+11   0.000     .1668032    .1668032
                    359  |  -.3495624    .106343    -3.29   0.001    -.5579909   -.1411339
                    384  |   1.532223    .106343    14.41   0.000     1.323795    1.740652
                    396  |  -.3163052    .106343    -2.97   0.003    -.5247337   -.1078766
                    400  |    2.04249   2.40e-13  8.5e+12   0.000      2.04249     2.04249
                    402  |   .8916416   2.40e-13  3.7e+12   0.000     .8916416    .8916416
                    406  |   .4219944   2.40e-13  1.8e+12   0.000     .4219944    .4219944
                    407  |  -.0054496   2.40e-13 -2.3e+10   0.000    -.0054496   -.0054496
                    408  |   1.256003    .106343    11.81   0.000     1.047575    1.464432
                    409  |  -.1215996    .106343    -1.14   0.253    -.3300281     .086829
                    410  |   -.638165   2.40e-13 -2.7e+12   0.000     -.638165    -.638165
                    411  |   1.002331    .106343     9.43   0.000      .793902    1.210759
                    413  |  -.0365287   2.40e-13 -1.5e+11   0.000    -.0365287   -.0365287
                    414  |   .6330768    .106343     5.95   0.000     .4246483    .8415053
                    415  |   1.186733    .106343    11.16   0.000     .9783047    1.395162
                    417  |   1.938914    .106343    18.23   0.000     1.730485    2.147343
                    418  |   .7328158    .106343     6.89   0.000     .5243872    .9412443
                    419  |  -1.964561   2.40e-13 -8.2e+12   0.000    -1.964561   -1.964561
                    420  |  -.6324252    .106343    -5.95   0.000    -.8408537   -.4239967
                    425  |   1.439779    .106343    13.54   0.000      1.23135    1.648207
                    433  |   .1288598    .106343     1.21   0.226    -.0795687    .3372883
                    440  |   .2761435    .106343     2.60   0.009      .067715     .484572
                    451  |   1.057055    .106343     9.94   0.000     .8486269    1.265484
                    453  |  -.5763308   2.40e-13 -2.4e+12   0.000    -.5763308   -.5763308
                    454  |   .7760571    .106343     7.30   0.000     .5676285    .9844856
                    464  |  -.4948954    .106343    -4.65   0.000    -.7033239   -.2864669
                    470  |   1.105564    .106343    10.40   0.000     .8971352    1.313992
                    474  |   .3041708    .106343     2.86   0.004     .0957423    .5125993
                    482  |  -.2833437   2.40e-13 -1.2e+12   0.000    -.2833437   -.2833437
                    492  |  -1.193162   2.40e-13 -5.0e+12   0.000    -1.193162   -1.193162
                    493  |   .1554492    .106343     1.46   0.144    -.0529793    .3638778
                    508  |  -.4405342    .106343    -4.14   0.000    -.6489627   -.2321056
                    600  |  -.5686236   2.40e-13 -2.4e+12   0.000    -.5686236   -.5686236
                    601  |   -.038786   2.40e-13 -1.6e+11   0.000     -.038786    -.038786
                    602  |  -1.312833    .106343   -12.35   0.000    -1.521262   -1.104405
                    604  |  -.1974843    .106343    -1.86   0.063    -.4059128    .0109443
                    606  |  -1.462773    .106343   -13.76   0.000    -1.671202   -1.254345
                    607  |  -.6652783   2.40e-13 -2.8e+12   0.000    -.6652783   -.6652783
                    623  |          0  (omitted)
                         |
nclassgoogle1#warepisode |
                    7 1  |          0  (empty)
                   16 2  |   .1748932    .106343     1.64   0.100    -.0335353    .3833218
                   29 2  |   1.293677    .106343    12.17   0.000     1.085249    1.502106
                   42 2  |  -.7241232    .106343    -6.81   0.000    -.9325518   -.5156947
                   49 2  |   .4218265    .106343     3.97   0.000      .213398    .6302551
                   51 1  |          0  (empty)
                   51 2  |          0  (omitted)
                   65 2  |    1.48965    .106343    14.01   0.000     1.281221    1.698078
                   72 2  |    .106077    .106343     1.00   0.319    -.1023515    .3145055
                   74 2  |   .8656148    .106343     8.14   0.000     .6571862    1.074043
                   75 2  |   .3534334    .106343     3.32   0.001     .1450049    .5618619
                   76 2  |  -.2778598    .106343    -2.61   0.009    -.4862883   -.0694313
                   81 2  |   .8075352    .106343     7.59   0.000     .5991066    1.015964
                   82 2  |   .4546747    .106343     4.28   0.000     .2462462    .6631032
                   83 2  |  -.2340618    .106343    -2.20   0.028    -.4424904   -.0256333
                   86 2  |  -.3589621    .106343    -3.38   0.001    -.5673907   -.1505336
                   89 2  |   .8553994    .106343     8.04   0.000     .6469708    1.063828
                   91 2  |  -.0075305    .106343    -0.07   0.944    -.2159591     .200898
                   92 2  |   .6100295    .106343     5.74   0.000      .401601    .8184581
                  100 2  |  -.3921308    .106343    -3.69   0.000    -.6005594   -.1837023
                  104 2  |   1.049439    .106343     9.87   0.000     .8410102    1.257867
                  105 2  |   1.192361    .106343    11.21   0.000     .9839327     1.40079
                  114 2  |  -.0872413    .106343    -0.82   0.412    -.2956698    .1211873
                  123 1  |          0  (empty)
                  123 2  |          0  (omitted)
                  124 1  |          0  (empty)
                  124 2  |          0  (omitted)
                  125 2  |  -.6770698    .106343    -6.37   0.000    -.8854984   -.4686413
                  128 2  |   .0637391    .106343     0.60   0.549    -.1446895    .2721676
                  140 2  |   1.536884    .106343    14.45   0.000     1.328456    1.745313
                  141 2  |   .7694682    .106343     7.24   0.000     .5610397    .9778967
                  142 2  |  -1.136175    .106343   -10.68   0.000    -1.344604   -.9277468
                  144 2  |  -.7918425    .106343    -7.45   0.000    -1.000271   -.5834139
                  147 2  |  -1.566815    .106343   -14.73   0.000    -1.775244   -1.358387
                  148 2  |   .5949771    .106343     5.59   0.000     .3865486    .8034056
                  152 1  |          0  (empty)
                  152 2  |          0  (omitted)
                  157 1  |          0  (empty)
                  157 2  |          0  (omitted)
                  164 2  |   .7218716    .106343     6.79   0.000      .513443    .9303001
                  173 2  |   .8054904    .106343     7.57   0.000     .5970618    1.013919
                  180 2  |   2.866755    .106343    26.96   0.000     2.658326    3.075183
                  184 2  |   1.153673    .106343    10.85   0.000     .9452448    1.362102
                  185 2  |  -.7705289    .106343    -7.25   0.000    -.9789575   -.5621004
                  187 2  |   .7912998    .106343     7.44   0.000     .5828713    .9997284
                  188 2  |   .8366582    .106343     7.87   0.000     .6282297    1.045087
                  192 2  |   1.548752    .106343    14.56   0.000     1.340324    1.757181
                  193 1  |          0  (empty)
                  193 2  |          0  (omitted)
                  194 1  |          0  (empty)
                  194 2  |          0  (omitted)
                  198 2  |   1.578429    .106343    14.84   0.000         1.37    1.786857
                  209 2  |   .1010288    .106343     0.95   0.342    -.1073998    .3094573
                  212 2  |   .3926219    .106343     3.69   0.000     .1841934    .6010504
                  213 2  |  -.1247769    .106343    -1.17   0.241    -.3332055    .0836516
                  221 2  |   1.855099    .106343    17.44   0.000      1.64667    2.063527
                  225 1  |          0  (empty)
                  225 2  |          0  (omitted)
                  226 1  |          0  (empty)
                  226 2  |          0  (omitted)
                  227 2  |    .558607    .106343     5.25   0.000     .3501785    .7670356
                  228 2  |   .4908554    .106343     4.62   0.000     .2824269     .699284
                  234 1  |          0  (empty)
                  234 2  |          0  (omitted)
                  235 2  |   1.445594    .106343    13.59   0.000     1.237166    1.654023
                  238 2  |   1.572318    .106343    14.79   0.000      1.36389    1.780747
                  239 2  |   .9909165    .106343     9.32   0.000      .782488    1.199345
                  241 2  |  -.3512804    .106343    -3.30   0.001    -.5597089   -.1428518
                  242 2  |   1.168841    .106343    10.99   0.000     .9604124    1.377269
                  244 2  |   2.927457    .106343    27.53   0.000     2.719029    3.135886
                  246 2  |   1.311626    .106343    12.33   0.000     1.103197    1.520054
                  251 2  |   .4436452    .106343     4.17   0.000     .2352167    .6520737
                  254 2  |   .2973793    .106343     2.80   0.005     .0889508    .5058079
                  258 1  |          0  (empty)
                  258 2  |          0  (omitted)
                  264 2  |   1.163462    .106343    10.94   0.000     .9550336    1.371891
                  266 2  |    .355159    .106343     3.34   0.001     .1467304    .5635875
                  267 2  |   .4135478    .106343     3.89   0.000     .2051193    .6219764
                  270 1  |          0  (empty)
                  270 2  |          0  (omitted)
                  271 2  |   1.666703    .106343    15.67   0.000     1.458275    1.875132
                  280 2  |    .454649    .106343     4.28   0.000     .2462205    .6630776
                  291 1  |          0  (empty)
                  291 2  |          0  (omitted)
                  293 1  |          0  (empty)
                  293 2  |          0  (omitted)
                  294 2  |   .3238531    .106343     3.05   0.002     .1154245    .5322816
                  295 2  |  -.5692931    .106343    -5.35   0.000    -.7777216   -.3608646
                  296 2  |   .8915181    .106343     8.38   0.000     .6830896    1.099947
                  298 2  |   .7320617    .106343     6.88   0.000     .5236332    .9404903
                  301 2  |   .4882896    .106343     4.59   0.000     .2798611    .6967182
                  303 1  |          0  (empty)
                  303 2  |          0  (omitted)
                  305 1  |          0  (empty)
                  305 2  |          0  (omitted)
                  351 1  |          0  (empty)
                  351 2  |          0  (omitted)
                  352 1  |          0  (empty)
                  352 2  |          0  (omitted)
                  353 1  |          0  (empty)
                  353 2  |          0  (omitted)
                  355 1  |          0  (empty)
                  355 2  |          0  (omitted)
                  359 2  |   .9110398    .106343     8.57   0.000     .7026113    1.119468
                  384 2  |    .617008    .106343     5.80   0.000     .4085794    .8254365
                  396 2  |    1.37198    .106343    12.90   0.000     1.163551    1.580408
                  400 1  |          0  (empty)
                  400 2  |          0  (omitted)
                  402 1  |          0  (empty)
                  402 2  |          0  (omitted)
                  406 1  |          0  (empty)
                  406 2  |          0  (omitted)
                  407 1  |          0  (empty)
                  407 2  |          0  (omitted)
                  408 2  |   .1523291    .106343     1.43   0.152    -.0560995    .3607576
                  409 2  |   1.017688    .106343     9.57   0.000     .8092591    1.226116
                  410 1  |          0  (empty)
                  410 2  |          0  (omitted)
                  411 2  |   .8220434    .106343     7.73   0.000     .6136149    1.030472
                  413 1  |          0  (empty)
                  413 2  |          0  (omitted)
                  414 2  |   1.302218    .106343    12.25   0.000      1.09379    1.510647
                  415 2  |   .3303033    .106343     3.11   0.002     .1218748    .5387318
                  417 2  |   .1833476    .106343     1.72   0.085     -.025081    .3917761
                  418 2  |    .244611    .106343     2.30   0.021     .0361824    .4530395
                  419 1  |          0  (empty)
                  419 2  |          0  (omitted)
                  420 2  |   1.093558    .106343    10.28   0.000     .8851295    1.301987
                  425 2  |   .4760244    .106343     4.48   0.000     .2675958    .6844529
                  433 2  |   .7447957    .106343     7.00   0.000     .5363672    .9532242
                  440 2  |    .015877    .106343     0.15   0.881    -.1925516    .2243055
                  451 2  |   .9514504    .106343     8.95   0.000     .7430218    1.159879
                  453 1  |          0  (empty)
                  453 2  |          0  (omitted)
                  454 2  |   .2046363    .106343     1.92   0.054    -.0037922    .4130648
                  464 2  |    1.28779    .106343    12.11   0.000     1.079361    1.496218
                  470 2  |    -.89908    .106343    -8.45   0.000    -1.107509   -.6906514
                  474 2  |    .779475    .106343     7.33   0.000     .5710464    .9879035
                  482 1  |          0  (empty)
                  482 2  |          0  (omitted)
                  492 1  |          0  (empty)
                  492 2  |          0  (omitted)
                  493 2  |   1.005661    .106343     9.46   0.000     .7972329     1.21409
                  508 2  |  -.8003432    .106343    -7.53   0.000    -1.008772   -.5919146
                  600 1  |          0  (empty)
                  600 2  |          0  (omitted)
                  601 1  |          0  (empty)
                  601 2  |          0  (omitted)
                  602 2  |   .8837213    .106343     8.31   0.000     .6752927     1.09215
                  604 2  |   .9100077    .106343     8.56   0.000     .7015792    1.118436
                  606 2  |   1.540137    .106343    14.48   0.000     1.331708    1.748566
                  607 1  |          0  (empty)
                  607 2  |          0  (omitted)
                  623 2  |          0  (omitted)
                         |
                   _cons |   1.618349    .131992    12.26   0.000     1.359649    1.877049
------------------------------------------------------------------------------------------

. parmest, saving("Estimates/EventStudyBroadControls.dta", replace)
(note: file Estimates/EventStudyBroadControls.dta not found)
file Estimates/EventStudyBroadControls.dta saved

. 
. poisson patentcount i.prosthetics##i.eventyear i.eventyear##i.warepisode i.nclassgoogle1##i.warepisode if medi
> calclass == 1, cluster(class_by_episode)
note: 623.nclassgoogle1 omitted because of collinearity
note: 351.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 351.nclassgoogle1#2.warepisode omitted because of collinearity
note: 600.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 600.nclassgoogle1#2.warepisode omitted because of collinearity
note: 601.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 601.nclassgoogle1#2.warepisode omitted because of collinearity
note: 607.nclassgoogle1#1.warepisode identifies no observations in the sample
note: 607.nclassgoogle1#2.warepisode omitted because of collinearity

Iteration 0:   log pseudolikelihood = -1577.0184  
Iteration 1:   log pseudolikelihood = -1513.4348  
Iteration 2:   log pseudolikelihood =  -1512.327  
Iteration 3:   log pseudolikelihood = -1512.3221  
Iteration 4:   log pseudolikelihood = -1512.3221  

Poisson regression                              Number of obs     =        448
                                                Wald chi2(14)     =          .
Log pseudolikelihood = -1512.3221               Prob > chi2       =          .

                                  (Std. Err. adjusted for 16 clusters in class_by_episode)
------------------------------------------------------------------------------------------
                         |               Robust
             patentcount |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
           1.prosthetics |  -1.537003   .2785576    -5.52   0.000    -2.082966   -.9910406
                         |
               eventyear |
                     88  |  -.6947287   .3234946    -2.15   0.032    -1.328766    -.060691
                     89  |  -1.084549   .6112435    -1.77   0.076    -2.282564    .1134665
                     90  |  -1.082359   .3464074    -3.12   0.002    -1.761305   -.4034131
                     91  |  -1.116896    .387787    -2.88   0.004    -1.876944   -.3568472
                     92  |  -.3907902   .1812079    -2.16   0.031    -.7459512   -.0356293
                     93  |  -.5945252   .2224186    -2.67   0.008    -1.030458   -.1585927
                     94  |  -.3008336    .329888    -0.91   0.362    -.9474023     .345735
                     95  |  -.0016414   .1295905    -0.01   0.990    -.2556341    .2523514
                     96  |  -.4552995   .1986565    -2.29   0.022    -.8446591   -.0659399
                     97  |   .2041274   .1790878     1.14   0.254    -.1468783    .5551331
                     98  |  -.0943153   .2571712    -0.37   0.714    -.5983615    .4097309
                     99  |  -.2797121   .3786093    -0.74   0.460    -1.021773    .4623485
                    101  |   .5939808   .2288994     2.59   0.009     .1453463    1.042615
                    102  |   .4670993   .2184048     2.14   0.032     .0390337    .8951649
                    103  |    .611917   .2126128     2.88   0.004     .1952036     1.02863
                    104  |   .8230929   .2694923     3.05   0.002     .2948976    1.351288
                    105  |   1.212172   .2852136     4.25   0.000     .6531634     1.77118
                    106  |   1.188628   .3184284     3.73   0.000       .56452    1.812736
                    107  |    1.05878   .3092148     3.42   0.001     .4527303     1.66483
                    108  |   .7424421   .2954701     2.51   0.012     .1633313    1.321553
                    109  |   .8776031   .2290333     3.83   0.000     .4287061      1.3265
                    110  |   .8412414   .2527196     3.33   0.001     .3459201    1.336563
                    111  |   .9132459   .3512075     2.60   0.009     .2248919      1.6016
                    112  |   .7415309   .3134907     2.37   0.018     .1271005    1.355961
                    113  |   1.512517   .4301422     3.52   0.000     .6694535     2.35558
                    114  |   1.160607   .2983393     3.89   0.000     .5758723    1.745341
                    115  |   .9804544   .1951521     5.02   0.000     .5979633    1.362945
                         |
   prosthetics#eventyear |
                  1  88  |   .0210787   .2297438     0.09   0.927    -.4292108    .4713683
                  1  89  |   .2795066   .3124154     0.89   0.371    -.3328163    .8918296
                  1  90  |   .2564478   .0746995     3.43   0.001     .1100395    .4028562
                  1  91  |   .5741208   .3033435     1.89   0.058    -.0204216    1.168663
                  1  92  |  -.5999043    .384836    -1.56   0.119    -1.354169    .1543605
                  1  93  |   -.394424    .223927    -1.76   0.078    -.8333129    .0444649
                  1  94  |  -.1881383   .1362201    -1.38   0.167    -.4551249    .0788482
                  1  95  |   .4321903   .1958183     2.21   0.027     .0483935    .8159871
                  1  96  |   .3476059   .3001172     1.16   0.247     -.240613    .9358248
                  1  97  |   .3848793   .1222578     3.15   0.002     .1452584    .6245002
                  1  98  |   .5666463   .2951679     1.92   0.055    -.0118722    1.145165
                  1  99  |   .2114984   .2929232     0.72   0.470    -.3626205    .7856172
                  1 101  |   .6051376   .2390407     2.53   0.011     .1366265    1.073649
                  1 102  |   .9029522   .1845153     4.89   0.000     .5413089    1.264595
                  1 103  |   1.478151   .1384993    10.67   0.000     1.206698    1.749605
                  1 104  |    1.36245   .2494898     5.46   0.000     .8734587    1.851441
                  1 105  |   .7764313   .3988428     1.95   0.052    -.0052862    1.558149
                  1 106  |   .9251724   .5948653     1.56   0.120    -.2407423    2.091087
                  1 107  |   .8939534   .5225296     1.71   0.087    -.1301858    1.918093
                  1 108  |   .0877929   .5633735     0.16   0.876    -1.016399    1.191985
                  1 109  |   .4258651   .4027191     1.06   0.290    -.3634498     1.21518
                  1 110  |  -.3428368   .3801877    -0.90   0.367    -1.087991    .4023175
                  1 111  |  -.1823075   .5048759    -0.36   0.718    -1.171846     .807231
                  1 112  |  -.1537273    .459091    -0.33   0.738    -1.053529    .7460745
                  1 113  |   -.607559   .4719782    -1.29   0.198    -1.532619    .3175013
                  1 114  |  -.6630051   .5240161    -1.27   0.206    -1.690058    .3640476
                  1 115  |  -.5943581   .1257342    -4.73   0.000    -.8407926   -.3479236
                         |
            2.warepisode |   1.789854   .2331101     7.68   0.000     1.332967    2.246742
                         |
    eventyear#warepisode |
                   88 2  |   .7491823   .3377701     2.22   0.027     .0871651    1.411199
                   89 2  |   .9632147   .6216238     1.55   0.121    -.2551455    2.181575
                   90 2  |   .9853447   .3529133     2.79   0.005     .2936473    1.677042
                   91 2  |    1.04178   .4025549     2.59   0.010     .2527866    1.830773
                   92 2  |   .3379168   .2369568     1.43   0.154    -.1265099    .8023435
                   93 2  |   .4837011   .2437127     1.98   0.047     .0060331    .9613692
                   94 2  |   .1748874   .3523503     0.50   0.620    -.5157066    .8654813
                   95 2  |  -.2111603    .200771    -1.05   0.293    -.6046642    .1823436
                   96 2  |    .123904   .2221433     0.56   0.577    -.3114888    .5592968
                   97 2  |  -.3375448   .2133655    -1.58   0.114    -.7557334    .0806439
                   98 2  |  -.0236413   .2715663    -0.09   0.931    -.5559016    .5086189
                   99 2  |   .2986432   .3888938     0.77   0.443    -.4635746    1.060861
                  101 2  |  -.6173721   .2467557    -2.50   0.012    -1.101004   -.1337398
                  102 2  |  -.4462688   .2333357    -1.91   0.056    -.9035985    .0110608
                  103 2  |  -.7015406   .2538915    -2.76   0.006    -1.199159   -.2039223
                  104 2  |  -.9192036   .2877181    -3.19   0.001    -1.483121   -.3552865
                  105 2  |  -1.305805   .3094321    -4.22   0.000    -1.912281    -.699329
                  106 2  |  -1.271965   .3447722    -3.69   0.000    -1.947706   -.5962241
                  107 2  |  -1.428501   .3369507    -4.24   0.000    -2.088913   -.7680901
                  108 2  |  -.9629015   .3204761    -3.00   0.003    -1.591023   -.3347799
                  109 2  |  -.8555602   .2540061    -3.37   0.001    -1.353403   -.3577174
                  110 2  |  -.8119416   .2859308    -2.84   0.005    -1.372356   -.2515276
                  111 2  |  -.7376344   .3705649    -1.99   0.047    -1.463928   -.0113407
                  112 2  |  -.5508308   .3427692    -1.61   0.108    -1.222646    .1209845
                  113 2  |  -1.417979   .4417166    -3.21   0.001    -2.283728   -.5522306
                  114 2  |  -.9311468   .3312805    -2.81   0.005    -1.580445    -.281849
                  115 2  |  -1.058927   .2469106    -4.29   0.000    -1.542863   -.5749915
                         |
           nclassgoogle1 |
                    351  |   .3347796   3.71e-15  9.0e+13   0.000     .3347796    .3347796
                    433  |  -.2526442   1.05e-11 -2.4e+10   0.000    -.2526442   -.2526442
                    600  |  -1.013867   5.16e-14 -2.0e+13   0.000    -1.013867   -1.013867
                    601  |  -.4840291   9.44e-14 -5.1e+12   0.000    -.4840291   -.4840291
                    602  |  -1.694337   4.09e-11 -4.1e+10   0.000    -1.694337   -1.694337
                    604  |  -.5789883   1.05e-11 -5.5e+10   0.000    -.5789883   -.5789883
                    606  |  -1.844278   1.32e-10 -1.4e+10   0.000    -1.844278   -1.844278
                    607  |  -1.110521   3.00e-14 -3.7e+13   0.000    -1.110521   -1.110521
                    623  |          0  (omitted)
                         |
nclassgoogle1#warepisode |
                  351 1  |          0  (empty)
                  351 2  |          0  (omitted)
                  433 2  |   .6810566   1.05e-11  6.5e+10   0.000     .6810566    .6810566
                  600 1  |          0  (empty)
                  600 2  |          0  (omitted)
                  601 1  |          0  (empty)
                  601 2  |          0  (omitted)
                  602 2  |   .8199822   4.09e-11  2.0e+10   0.000     .8199822    .8199822
                  604 2  |   .8462687   1.05e-11  8.1e+10   0.000     .8462687    .8462687
                  606 2  |   1.476398   1.32e-10  1.1e+10   0.000     1.476398    1.476398
                  607 1  |          0  (empty)
                  607 2  |          0  (omitted)
                  623 2  |   .0423039   .0775527     0.55   0.585    -.1096966    .1943043
                         |
                   _cons |   2.195424   .2204293     9.96   0.000     1.763391    2.627458
------------------------------------------------------------------------------------------

. parmest, saving("Estimates/EventStudyMedicalControls.dta", replace)
(note: file Estimates/EventStudyMedicalControls.dta not found)
file Estimates/EventStudyMedicalControls.dta saved

. 
. 
. 
. use "Estimates/EventStudyMedicalControls.dta", clear

. rename estimate prostheticestimate

. label var prostheticestimate "Prosthetics Patents"

. label var min95 "Prosthetics Lower"

. label var max95 "Prosthetics Upper"

. drop z p stderr eq

. 
. keep if substr(parm,1,13) == "1.prosthetics"
(147 observations deleted)

. replace parm = "1.prosthetics#100o.eventyear" if parm == "1.prosthetics"
(1 real change made)

. replace max95 = 0 if parm == "1.prosthetics#100o.eventyear"
(1 real change made)

. replace min95 = 0 if parm == "1.prosthetics#100o.eventyear"
(1 real change made)

. replace prostheticestimate = 0 if parm == "1.prosthetics#100o.eventyear"
(1 real change made)

. 
. gen eventyear = .
(28 missing values generated)

. lab var eventyear "Event Year"

. gen eventyearB = ""
(28 missing values generated)

. replace eventyearB = substr(parm,15,3)
variable eventyearB was str1 now str3
(28 real changes made)

. replace eventyearB = substr(parm,15,2) if substr(parm,17,1) == "o"
(0 real changes made)

. destring eventyearB , gen(eventyearC)
eventyearB: all characters numeric; eventyearC generated as int

. replace eventyear = eventyearC - 100 
(28 real changes made)

. // generates Figure D.1 
. graph twoway scatter prostheticestimate eventyear if eventyear >= -12 & eventyear <= 12, || ///
>         lfit prostheticestimate eventyear if eventyear >= -12 & eventyear <= 0, lpattern(dash)  || ///
>         rcap min95 max95 eventyear if eventyear >= -12 & eventyear <= 12,  ///
>  xline(0, lcolor(black) lpattern(dash)) ///
>  yline(0, lcolor(black)) ///
>  title("Other Medical Controls", size(medlarge)) ///
>  ylabel(-2 "-2" -1 "-1" 0.0 "0.0"  1 "1" 2 "2") ///
>  legend(order(1 "Prosthetic Patenting Rate" 2 "Trend through Baseline Estimates") rows(1)) ///
>  xtitle("") ytitle("Change in Patenting Rate") graphregion(color(white)) /// 
>  xlabel(-12(6)12, labsize(medsmall)) xscale(range(-12 12)) ///
>  name(EventStudyMedicalControls, replace)

. 
. graph export "Figures/EventStudyMedicalControls.pdf", name(EventStudyMedicalControls)  replace
(file /Users/parkerrogers/Dropbox/MedicalInnovationProjects/CivilWarProject/Restat_Replication/Figures/EventStud
> yMedicalControls.pdf written in PDF format)

. 
.  
. use "Estimates/EventStudyBroadControls.dta", clear

. rename estimate prostheticestimate

. label var prostheticestimate "Prosthetics Patents"

. label var min95 "Prosthetics Lower"

. label var max95 "Prosthetics Upper"

. drop z p stderr eq

. 
. keep if substr(parm,1,13) == "1.prosthetics"
(480 observations deleted)

. replace parm = "1.prosthetics#100o.eventyear" if parm == "1.prosthetics"
(1 real change made)

. replace max95 = 0 if parm == "1.prosthetics#100o.eventyear"
(1 real change made)

. replace min95 = 0 if parm == "1.prosthetics#100o.eventyear"
(1 real change made)

. replace prostheticestimate = 0 if parm == "1.prosthetics#100o.eventyear"
(1 real change made)

. 
. gen eventyear = .
(28 missing values generated)

. lab var eventyear "Event Year"

. gen eventyearB = ""
(28 missing values generated)

. replace eventyearB = substr(parm,15,3)
variable eventyearB was str1 now str3
(28 real changes made)

. replace eventyearB = substr(parm,15,2) if substr(parm,17,1) == "o"
(0 real changes made)

. destring eventyearB , gen(eventyearC)
eventyearB: all characters numeric; eventyearC generated as int

. replace eventyear = eventyearC - 100 
(28 real changes made)

. // generates Figure D.1 
. graph twoway scatter prostheticestimate eventyear if eventyear >= -12 & eventyear <= 12,  || ///
>         lfit prostheticestimate eventyear if eventyear >= -12 & eventyear <= 0, lpattern(dash)  || ///
>         rcap min95 max95 eventyear if eventyear >= -12 & eventyear <= 12,  ///
>  xline(0, lcolor(black) lpattern(dash)) ///
>  yline(0, lcolor(black)) ///
>  title("Broadest Set of Controls", size(medlarge)) ///
>  ylabel(-2 "-2" -1 "-1" 0.0 "0.0"  1 "1" 2 "2") ///
>  legend(order(1 "Prosthetic Patenting Rate" 2 "Trend through Baseline Estimates") rows(1)) ///
>  xtitle("") ytitle("Change in Patenting Rate") graphregion(color(white)) /// 
>  xlabel(-12(6)12, labsize(medsmall)) xscale(range(-12 12)) ///
>  name(EventStudyBroadControls, replace)

. 
.  graph export "Figures/EventStudyBroadControls.pdf", name(EventStudyBroadControls)  replace
(file /Users/parkerrogers/Dropbox/MedicalInnovationProjects/CivilWarProject/Restat_Replication/Figures/EventStud
> yBroadControls.pdf written in PDF format)

. 
.         
.  
. 
. capture log close
